双指数平滑法和线性回归法在 PT.

Sherly Indriani Rahayu, Jauhari Arifin
{"title":"双指数平滑法和线性回归法在 PT.","authors":"Sherly Indriani Rahayu, Jauhari Arifin","doi":"10.37090/indstrk.v7i3.1095","DOIUrl":null,"url":null,"abstract":"PT. XYZ is one of the company that produces packaging materials, one of which is sacks. This study aims to determine forecasting on sack raw material packaging using the Double Exponential Smoothing method and Linear Regression in these calculations using manual calculation methods using Microsoft excel. The two methods are then identified as having the smallest error value. The data used in this study uses secondary data in the form of sales reports of raw material packaging in the past. Based on the forecasting results obtained using the Double Exponential Smoothing and Linear Regression methods, the smallest error value was obtained in the linear regression method with an error value of 275,711. The forecasting results in the next period were 16,713 by manual calculation. Thus, among the predicted results of the two methods, the linear regression method is the most optical. Keywords: Double Exponential Smoothing; Forecasting; Regresi Linier","PeriodicalId":499831,"journal":{"name":"Industrika","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Penerapan Metode Double Exponential Smoothing dan Regresi Linier pada Peramalan Persediaan Packaging di PT. XYZ\",\"authors\":\"Sherly Indriani Rahayu, Jauhari Arifin\",\"doi\":\"10.37090/indstrk.v7i3.1095\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"PT. XYZ is one of the company that produces packaging materials, one of which is sacks. This study aims to determine forecasting on sack raw material packaging using the Double Exponential Smoothing method and Linear Regression in these calculations using manual calculation methods using Microsoft excel. The two methods are then identified as having the smallest error value. The data used in this study uses secondary data in the form of sales reports of raw material packaging in the past. Based on the forecasting results obtained using the Double Exponential Smoothing and Linear Regression methods, the smallest error value was obtained in the linear regression method with an error value of 275,711. The forecasting results in the next period were 16,713 by manual calculation. Thus, among the predicted results of the two methods, the linear regression method is the most optical. Keywords: Double Exponential Smoothing; Forecasting; Regresi Linier\",\"PeriodicalId\":499831,\"journal\":{\"name\":\"Industrika\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-10-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Industrika\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.37090/indstrk.v7i3.1095\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Industrika","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.37090/indstrk.v7i3.1095","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

XYZ是一家生产包装材料的公司,其中一种是麻袋。本研究的目的是利用双指数平滑法和线性回归来确定麻袋原料包装的预测,在这些计算中使用Microsoft excel手工计算方法。然后确定这两种方法具有最小的误差值。本研究使用的数据采用二手数据的形式,在过去的原材料包装销售报告。结合双指数平滑法和线性回归法的预测结果,线性回归法的误差值最小,误差值为275,711。人工计算下一期预测结果为16,713。因此,在两种方法的预测结果中,线性回归方法是最直观的。关键词:双指数平滑;预测;Regresi划线的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Penerapan Metode Double Exponential Smoothing dan Regresi Linier pada Peramalan Persediaan Packaging di PT. XYZ
PT. XYZ is one of the company that produces packaging materials, one of which is sacks. This study aims to determine forecasting on sack raw material packaging using the Double Exponential Smoothing method and Linear Regression in these calculations using manual calculation methods using Microsoft excel. The two methods are then identified as having the smallest error value. The data used in this study uses secondary data in the form of sales reports of raw material packaging in the past. Based on the forecasting results obtained using the Double Exponential Smoothing and Linear Regression methods, the smallest error value was obtained in the linear regression method with an error value of 275,711. The forecasting results in the next period were 16,713 by manual calculation. Thus, among the predicted results of the two methods, the linear regression method is the most optical. Keywords: Double Exponential Smoothing; Forecasting; Regresi Linier
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Penerapan Metode Double Exponential Smoothing dan Regresi Linier pada Peramalan Persediaan Packaging di PT. XYZ Perbandingan Peramalan Permintaan Produk Hollow Alumunium Menggunakan Metode Single Moving Average Dan Exponential Smoothing Pada PT. MU Analisis Pengukuran Waktu Baku Untuk Menentukan Tingkat Produktivitas Pada Operator Pemasangan O-Ring Menggunakan Metode Jam Henti (Studi Kasus Di PT Y) Perencanaan Jadwal Perawatan Pencegahan Mesin Sliting Dengan Metode RCM (Realibility Centered Maintenance) Di PT. XYZ Penerapan Quality Function Deployment (QFD) Dalam Mendesain Ulang Alat Cabut Singkong Otomatis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1